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» A Training Method with Small Computation for Classification
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ACL
2012
11 years 11 months ago
Prediction of Learning Curves in Machine Translation
Parallel data in the domain of interest is the key resource when training a statistical machine translation (SMT) system for a specific purpose. Since ad-hoc manual translation c...
Prasanth Kolachina, Nicola Cancedda, Marc Dymetman...
CVPR
2008
IEEE
14 years 11 months ago
Simultaneous super-resolution and feature extraction for recognition of low-resolution faces
Face recognition degrades when faces are of very low resolution since many details about the difference between one person and another can only be captured in images of sufficient...
Pablo H. Hennings-Yeomans, Simon Baker, B. V. K. V...
PRL
2010
209views more  PRL 2010»
13 years 3 months ago
Efficient update of the covariance matrix inverse in iterated linear discriminant analysis
For fast classification under real-time constraints, as required in many imagebased pattern recognition applications, linear discriminant functions are a good choice. Linear discr...
Jan Salmen, Marc Schlipsing, Christian Igel
ICPR
2004
IEEE
14 years 10 months ago
Direct Condensing: An Efficient Voronoi Condensing Algorithm for Nearest Neighbor Classifiers
Voronoi condensing reduces training patterns of nearest neighbor classifiers without changing the classification boundaries. This method plays important roles not only in the near...
Takekazu Kato, Toshikazu Wada
ICPR
2004
IEEE
14 years 10 months ago
Selective Sampling Based on the Variation in Label Assignments
In this paper, a new selective sampling method for the active learning framework is presented. Initially, a small training set ? and a large unlabeled set ? are given. The goal is...
Piotr Juszczak, Robert P. W. Duin